DEVELOPMENT AND TESTING OF THE PC-MET (PERSON-CENTERED MEASURE EVALUATION TOOL)

Abstract Despite the importance of person-centered measurement -- and that numerous research instruments are now available to measure person-centeredness -- there are no tools to evaluate the extent to which existing research instruments themselves are developed consistent with principles of person-centeredness. The PC-MET (Person-Centered Measure Evaluation Tool) was developed to fill that gap. Based on literature and theory, the PC-MET assesses the process of instrument development and the content of the instrument itself based on six overarching criteria of person-centeredness: co-creation, accommodation, incorporation, biopsychosocial-cultural components, pragmatism, and systemic focus. The inter-rater reliability of the PC-MET was evaluated based on instruments recommended for use in relation to the Alzheimer’s Association 2018 Dementia Care Practice Recommendations (DCPR). Independent raters evaluated two measures within each DCPR area using the PC-MET. Agreement was excellent (kappas>0.81) across all PC-MET criteria with the exception of the criteria assessing biopsychosocial-cultural components (where agreement was moderate; kappa=0.42) and pragmatism (where agreement was substantial; kappa=0.68). Raters provided feedback on the PC-MET and agreed or strongly agreed that the tool is easy to understand and score; the six PC-MET criteria are relevant and complete; and the PC-MET could improve the person-centeredness of dementia measurement instruments. The PC-MET has broad potential use, including to critique the extent to which existing instruments are person-centered, to promote efforts to make existing measures more person-centered, and to inform the development of new person-centered measures. This work was supported by the NIA through a grant to the Alzheimer’s Association and by the LINC-AD Research Steering Committee.


THE CHALLENGES OF LARGE QUALITATIVE DATASETS AND MEETING THE EXPECTATIONS OF INDIGENOUS COMMUNITIES AND FUNDERS Jordan Lewis, University of Minnesota Medical School, Duluth campus, Duluth, Minnesota, United States
Literature on Alaska Native Elders and how they subjectively define a successful older age is limited.The lack of a culturally specific definition often results in the use of a generic definition that portrays Alaska Native Elders as aging less successfully than their White or non-Native counterparts.However, there is very little understanding of the diverse array of successful aging experiences and how this data will translate to other racial and ethnic minority populations, as well as advance the field of successful aging.This decade long study research the concept of successful aging from an Alaska Native perspective, or what it means to age well in Alaska Native communities and the lessons Elders.Qualitative, in-depth, interviews have been conducted with 154 Elders representing 20 participating communities to explore the concept of successful aging and the role of their community in the aging process.This study highlights the four (6) elements of successful aging, or "Eldership:" emotional wellbeing, spirituality, community engagement, Native ways of life, generativity, and physical health.These elements serve as the foundation of how communities define who is an Elder and what is important when considering who has aged successfully or not.This presentation will discuss challenges of analyzing large datasets to inform future studies, the development of a theory and measure of successful aging, as well as how to balance the needs of Indigenous community partners and the funders.

IMPROVING ASSESSMENT, EDUCATION, AND TRAINING
Abstract citation ID: igad104.0989Despite the importance of person-centered measurement --and that numerous research instruments are now available to measure person-centeredness --there are no tools to evaluate the extent to which existing research instruments themselves are developed consistent with principles of person-centeredness.The PC-MET (Person-Centered Measure Evaluation Tool) was developed to fill that gap.Based on literature and theory, the PC-MET assesses the process of instrument development and the content of the instrument itself based on six overarching criteria of personcenteredness: co-creation, accommodation, incorporation, biopsychosocial-cultural components, pragmatism, and systemic focus.The inter-rater reliability of the PC-MET was evaluated based on instruments recommended for use in relation to the Alzheimer's Association 2018 Dementia Care Practice Recommendations (DCPR).Independent raters evaluated two measures within each DCPR area using the PC-MET.Agreement was excellent (kappas>0.81)across all PC-MET criteria with the exception of the criteria assessing biopsychosocial-cultural components (where agreement was moderate; kappa=0.42)and pragmatism (where agreement was substantial; kappa=0.68).Raters provided feedback on the PC-MET and agreed or strongly agreed that the tool is easy to understand and score; the six PC-MET criteria are relevant and complete; and the PC-MET could improve the person-centeredness of dementia measurement instruments.The PC-MET has broad potential use, including to critique the extent to which existing instruments are person-centered, to promote efforts to make existing measures more person-centered, and to inform the development of new person-centered measures.This work was supported by the NIA through a grant to the Alzheimer's Association and by the LINC-AD Research Steering Committee.Delirium is a common and serious geriatric syndrome, especially in older adults with cognitive impairment.Accurate caregiver assessment and reporting of delirium in community-dwelling older adults can help healthcare providers diagnose and treat delirium more effectively.Yet, caregivers often lack confidence in their ability to accurately assess and report delirium.An automated method to detect the presence and symptoms of delirium could potentially boost caregiver confidence and assist with more accurate delirium assessment and reporting.This study explored the use of ChatGPT, a generative AI based on the Large Language Model (LLM), to detect the presence and symptoms of delirium.We trained ChatGPT using a series of prompts specifically designed to enhance its understanding of the domain knowledge and the scoring mechanism of a caregiver-centered, seven-item delirium assessment, the Sour Seven.The trained ChatGPT model was asked to identify and score various delirium symptoms in five previously validated geriatric case vignettes using the Sour Seven scale.Each case was repeated three times to test for reliability.The ChatGPT assessment results were compared against those of human experts.The preliminary analysis showed that items 3, 6 and 7 were scored correctly in all cases, but mixed results were found on items 1, 2, 4, and 5, mostly because the AI applied a single symptom statement to multiple items.Overall, the results indicate that generative AI has the potential to accurately capture and represent complex delirium symptoms in natural language, which could assist caregivers in accurately identifying and reporting delirium symptoms.Quizzing is an understudied communication behavior used by care partners during in-home dementia care interactions.The aim of this study was to characterize and describe the behavior, identify types, characterize care situations, and determine how people living with dementia react to quizzing.Forty video observations of in-home interactions were coded to determine relationships between care partner quizzing and the person with dementia's reactions and analyzed using sequential behavioral analysis.Ten case studies with high instances of quizzing were examined for interpersonal context.Quizzing was defined as a series of rapid questions by the care partner that most often appeared to test the memory or knowledge of the person with dementia.Instances of quizzing that included long-term and short-term memory checks were most likely to elicit a negative reaction from the person with dementia (resistiveness, distress, and apathy).Long-term memory check always preceded resistiveness and distress (CP=1.0)and apathy preceded long-term memory check short-term memory check (CP = 0.71, 0.21).Quizzing used for distraction or reminiscing appeared to elicit positive responses from the person with dementia.Distraction and mutual reminiscing always followed cooperation (CP=1.0).Case study results indicated the care partners seemed to be testing the abilities of the person with dementia; possibly to alleviate or reverse dementia symptoms.Additional research is warranted to understand the use of quizzing during in-home care.The use of behavioral coding, sequential analysis, and case study examination can provide evidence of communication best practices to develop communication training for dementia care dyads.

DEVELOPMENT AND TESTING OF THE PC-MET (PERSON-CENTERED MEASURE EVALUATION TOOL)
Abstract citation ID: igad104.0992

MENTAL HEALTH FIRST AID TRAINING: EVIDENCE OF ITS EFFECTIVENESS FOR MENTAL HEALTH PROMOTION AMONG OLDER ADULTS Iftekhar Amin, University of North Texas at Dallas, Dallas, Texas, United States
Background: About 15% of adults aged 60 and over have a mental health disorder.However, stigma and lack of knowledge of mental health resources act as barriers for them to seek professional help.Mental Health First Aid (MHFA) is an evidence-based program that teaches participants how to identify, understand and respond to signs of mental illnesses and substance use disorders.The Older Adults version of this training focuses on the unique experiences and needs of older adults.This study evaluated the effectiveness of a Substance Abuse and Mental Health Services Administration (SAMHSA) funded MHFA training program among older adults.Method: Data were collected from MHFA training sessions delivered to 27 staff and 36 residents at two assisted living facilities from January to March 2023.A

EXPLORING THE POTENTIAL OF CHATGPT FOR ASSESSING DELIRIUM SYMPTOMS IN OLDER ADULTS WITH COGNITIVE IMPAIRMENT Yong
Kyung Choi 1 , and Shih-Yin Lin 2 , 1. University of Pittsburgh, Pittsburgh, Pennsylvania, United States, 2. NYU Rory Meyers College of Nursing, New York City, New York, United States

FAMILY QUIZZING BEHAVIOR DURING IN-HOME DEMENTIA CARE: A SEQUENTIAL BEHAVIORAL ANALYSIS WITH VIDEO CASE STUDIES
Carissa Coleman 1 , Paige Wilson 2 , and Kristine Williams 3 , 1. University of Kansas, Kansas City, Kansas, United States, 2. The University of Kansas, West Palm Beach, Florida, United States, 3. University of Kansas Medical Center, Kansas City, Kansas, United States